This section is intended to introduce various aspects of the art, which may be associated with embodiments of the disclosed techniques. This discussion is believed to assist in providing a framework to facilitate a better understanding of particular aspects of the disclosed techniques. Accordingly, it should be understood that this section is to be read in this light, and not necessarily as admissions of prior art.
Seismic interpretation generally involves a person skilled in geologic interpretation, referred to as an interpreter, who manually identifies seismic horizons by reviewing seismic reflections and mapping the seismic reflections into seismic horizons. A seismic horizon may include boundaries in the subsurface structures that are deemed important by an interpreter. Finding the seismic horizon can be a subjective, time consuming process.
Tool sets for computer-aided volume interpretation typically include horizon tracking techniques that are used to determine seismic horizons. One horizon tracking technique may follow the peaks of seismic amplitudes, beginning with a user provided seed point in a vertical seismic section. The vertical seismic section can be either a cross-line vertical section in the y-z plane or an in-line vertical section in the x-z plane.
Another horizon tracking technique is known as “seed detection,” which is a technique for growing a region in a three dimensional seismic data volume. Seed detection may result in a set of connected voxels in a 3D seismic data volume that fulfills user-specified attribute criteria. To find the set of connected voxels, seed detection may begin with a point in a data volume that connects with admissible neighbors in order to fully define the connected voxels. Admissible neighbors are the points that meet some user defined criteria that surround the starting point. The new points are added to the current connected voxels and the procedure continues until it reaches a point where no further admissible neighbors exist.
An example of a horizon tracking technique is discussed in United States Patent Application Publication No. 2008/0285384 by James. The application discloses a seed picking algorithm that can use a first point for picking a set of second points from a data set. Each of the points in the set of second points can be redefined as the first point, and the algorithm may repeat. An iteration number or other attribute can be assigned to the points and the iteration number can correspond to the number of times the algorithm has been repeated to process the point. The attribute or a number of attributes can be displayed as a visual characteristic for each point. An iterative process can be applied to a set of seismic data points, starting at a seed data point and finding a set of next iteration seed points from the set of points neighboring the seed point, continuing only with next iteration seed points. The number of points that are found by the process when the point is used as a seed data point can be recorded for each of a set of data points.
International Patent Application Publication No. 2010/047856 by Mark Dobin et al. discloses a method and system that may identify a geologic object through cross sections of a geologic data volume. The method includes obtaining a geologic data volume having a set of cross sections. Then, two or more cross sections can be selected, and a transformation vector can be estimated between the cross sections. Based on the transformation vector, a geologic object can be identified within the geologic data volume.
The existing techniques described above tend to find geologic objects, including horizons, without addressing the uncertainty or consistency associated with the resulting geologic objects. Even when multiple seeds are used, the existing techniques offer little insight to the relationships or consistencies among the seeds.